Urban-Rural Inequalities in Potentially Preventable Hospital Admissions

Carolyn Hunter-Rowe Senior Health Intelligence Analyst

Department of Public HealthNHS Dumfries and Galloway

Potentially Preventable Admissions

“represent a range of conditions that result from medical problems that may be preventable with the application of public health measures or through early disease management and treatment in primary care.”

[Agency for Healthcare Research and Quality, 2007]

Background

• Concept of avoidable / preventable admissions population-based health improvement e.g. alcohol,

smoking prevention of adverse events – accidents, injuries,

falls intervention in primary care – ambulatory care

sensitive conditions (ACSCs)

• Ambulatory care sensitive conditions Vaccine-preventable e.g. influenza, bacterial

pneumonia Acute medical e.g. cellulitis, dehydration,

gastroenteritis Chronic conditions e.g. angina, COPD, diabetes

• Indicator of avoidable morbidity and the accessibility and quality of primary health care

Potentially Preventable Admissions by Main Diagnosis Group, NHS Scotland, 2009/10

n = 85,721

Context

• Environment / setting is a key determinant of health and wellbeing

“where people live affects their health and chances of leading flourishing lives” [CSDH, 2008]

• Inequalities between urban-rural areas in UK and Scotland self-reported health [Levin 2003, Riva et al. 2009] cancer [Campbell et al. 2001] ischaemic heart disease [Levin & Leyland 2006]

• International literature – mixed evidence re PPAs, generally positive association with rurality

Study Aims

1. To determine whether the prevalence of hospital admissions for potentially preventable conditions is associated with urban or rural area of residence in Dumfries and Galloway.

2. To determine the extent to which any differences are explained by deprivation after controlling for differences in the study populations.

Methodology

• Data Source - SMR01, Apr 2005 to Mar 2010

• Primary outcome - rate of admission

• Standardised Admission Ratios (SARs)

• Negative binomial regression

• Independent variables: age, sex, socio-economic status, co-morbidities, urban-rural classification, distance to hospital, drive to GP

• Incidence Rate Ratios (IRRs) - relative risk of admission

Setting

Study cohort

• 193 datazones: 102 urban, 91 rural

• 18,675 hospital admissions over 5 year period

• 48% male, 52% female

• Mean age 47.0 years (M) and 49.0 years (F)

• 13.7% resided in most deprived quintile, 5.5% least deprived (SIMD09)

• Area of residence 59.5% urban, 40.5% rural

Standardised Admission Ratios

SAR: Urban 112.1, Rural 87.3 (p<0.0001).

Correlation between Standardised Admission Ratios and SIMD Score

0

50

100

150

200

0

50

100

150

200

0

50

100

150

200

0 20 40 60 0 20 40 60

0 20 40 60

Urban: r=0.63, 95% CI 0.50,0.74, p<0.0001 Rural: r=0.51, 95% CI 0.34,0.65, p<0.0001

All: r=0.51, 95% CI 0.52,0.70, p<0.0001SA

R

SIMD Score

Predictors of Preventable Admissions

Variable (reference)

Incidence Rate Ratio (95% CI)

Model 1: Age Model 2: Age, SIMD

Model 3: Age, SIMD, Distance

Urban 1.00 1.00 1.00

Rural 0.77 (0.71, 0.84)

0.80 (0.75, 0.86)

0.85 (0.79, 0.92)

Age 0-15 1.00 1.00 1.00

16-44 0.61 (0.57, 0.65)

0.61 (0.58, 0.65)

0.61 (0.58, 0.65)

45-64 0.58 (0.54, 0.62)

0.59 (0.55, 0.63)

0.59 (0.56, 0.63)

65-74 1.11 (1.03, 1.20)

1.13 (1.05, 1.22)

1.14 (1.05, 1.23)

75+ 2.17 (2.01, 2.36)

2.23 (2.06, 2.42)

2.25 (2.08, 2.43)

SIMD09 1 - most 1.00 1.00

2 0.79 (0.71, 0.88)

0.80 (0.71, 0.89)

3 0.72 (0.65, 0.80)

0.72 (0.64, 0.80)

4 0.62 (0.56, 0.69)

0.61 (0.54, 0.68)

5 - least 0.54 (0.45, 0.64)

0.52 (0.45, 0.62)

results significant at p=0.05 highlighted in bold

Adjusted admission rates by age group and urban-rural category

0.0

0.5

1.0

1.5

2.0

2.5

3.0

0-15 yrs 16-44 yrs 45-64 yrs 65-74 yrs 75+ yrs

Age group

Inci

den

ce R

ate

Rat

io

Urban Rural

Adjusted admission rates by area-based deprivation and urban-rural category

0.00

0.25

0.50

0.75

1.00

1.25

1.50

1 2 3 4 5

SIMD09 Quintile (1= most deprived, 5= least deprived)

Inci

den

ce R

ate

Rat

io

Urban Rural

Main Findings

• Inequalities in potentially preventable admissions within both urban and rural areas

• Adjusted admission rates 15% lower in rural areas compared to urban areas

• Risk of admission higher in the most deprived quintile compared to the least deprived

• Significant positive association with deprivation in both urban and rural areas

• Higher admission rates for the elderly population in rural areas

Conclusions

• Large proportion of variation in potentially preventable admissions accounted for by socio-demographic factors and accessibility to services

• Evidence of inequalities in potentially preventable admissions should be used to inform healthcare strategy and service development.

• Importance of understanding geographic inequalities within local context to ensure service provision meets health needs of the population

• Larger study could explore intra-rural variations that were outwith the scope of this research

Acknowledgements

University of Manchester• Dr Isla Gemmell• Abdelouahid Tajar

NHS Dumfries and Galloway• Dr Andrew Carnon• Elisabeth Smart